The New Language of Customer Engagement

Artificial intelligence (AI), an inevitable part of our lives now, can actually be the answer to keeping pace with your customers’ ever-increasing demands.

Keeping your customer happy requires going beyond the transactional nature of a deal. Building this relationship, however, can be challenging. 

An AI-powered customer relationship management (CRM) system might just be the solution. 

When adopted, it is not just a data reservoir but an independent, virtual sales assistant. For example, AI can provide customer-specific recommendations with the help of smart assistants, which can provide a personalized experience to the customers and keep them engaged.

So let’s learn more about how you can use AI in CRM to engineer the perfect customer connection.

AI in CRM: the next big digital revolution 

AI uses countless data points to understand and predict customer behavior and offers tailored suggestions to sales reps without needing them to sift through a plethora of historical records manually.

Imagine the following scenario: your sales team has instant access to insights about customer behavior, buying patterns, and potential pain points. This would be all thanks to using AI in CRM. 

An AI-powered CRM solution can instantly boost metrics like engagement, conversion, and retention rates.

Supporting the above information is data showing:

  • AI in CRM can help reduce customer acquisition costs by up to 23%.
  • Companies that utilize AI in their CRM systems see a 74% increase in customer engagement rates.
  • AI-driven CRMs can reduce lead response time by 61%.
  • 61% of businesses believe that AI-powered CRMs help in better understanding customer needs.

Using AI in CRM is not just an upgrade but can transform your business operations from traditional to AI-centric. It will enable your sales reps to move from struggling to manage their workflow, maybe due to admin tasks that can be automated via AI, to focusing on what really matters – closing deals and building relationships. 

With AI’s abilities to analyze vast amounts of data you can actually remain competitive and be ready to adapt to the changing preferences of your customers at a moment’s notice.

This is not all. AI in CRM systems has led to the development of conversational sales assistants. Conversational AI in present-day CRM tools uses natural language processing (NLP) and machine learning, allowing your business to interact with customers through chatbots and virtual assistants and get better at the customer communication game with AI. 

These technologies can handle a wide range of tasks, from answering FAQs and providing product recommendations to managing bookings to troubleshooting issues. By offering 24/7 support, they not only improve your customer satisfaction scores but also reduce response times.

Integrating conversational AI into CRM systems is a step towards building stronger customer relationships and increasing operational efficiency. 

If you aren’t yet sold on the idea of using AI in CRM, let’s delve deeper into some other benefits.

Unlocking the benefits of AI in CRM

If we look from a salesperson’s point of view, AI offers various benefits, like smarter workflows, insights to help them better understand customers, and even the ability to predict possible pain points in the customer’s buying journey.

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Customers, too, benefit from having AI power your CRM system.

AI ensures a seamless journey for your customers from start to finish. For example, with the help of chatbots and conversational AI, your customers can now rely on timely and relevant communication. Also, since AI-powered CRM complies with high standards of data privacy, your customers can be assured that their data isn’t misused.

The benefits can be broadly classified into the following.

  • Enhance personalization with predictive insights
  • Automate repetitive actions and save time
  • Elevate use experience with contextual AI

Enhanced personalization with predictive insights

A major selling point of AI in CRM is its ability to provide a personalized experience for your customers. 

With the help of AI-driven predictive analytics, businesses can anticipate what a customer wants based on their behavior patterns and buying histories. This helps your sales rep adopt a proactive approach when addressing concerns customers might raise.

Other than this, your company can also use this data to create a targeted marketing campaign that is highly personalized to your customers, leading to the benefits of better return on investment (ROI) and conversion rates for your business. 

For example, if your customer is stuck at the deal closure stage in their buying journey, AI can prompt you to send a discount or offer reminder emails to trigger the purchase.

Increase customer engagement with personalization

Suppose you own a retail shop. You would think about offering your customer a message on their birthday offering them a discount on their purchases. In another instance, a customer abandons their card mid-way through their purchase. You send a reminder email while offering a time-based offer to lure them back in.

Do these scenarios sound familiar? These are some examples of marketing strategies that AI can automate that are timely, relevant, and personalized, leading to better engagement. In fact, research shows that 71% of buyers want companies to deliver personalized customer interactions, while four in five marketers see a positive ROI when they use personalization.

Now, with better engagement, you can increase customer loyalty, which in turn reduces customer churn. AI chatbots play a major role in helping companies achieve this. 

Customers’ queries and concerns can now be answered by a conversational AI assistant that works around the clock. Other AI tech can help you establish an omnichannel presence. By interacting with customers via call, email, and other channels, you can streamline the data from all channels and offer an integrated and unified experience for them. 

Automate repetitive actions and save time 

The goal of AI is not just to mimic humans but to simplify their work. 

In a traditional CRM, salespeople spend a significant chunk of their time performing repetitive tasks such as sending emails, scheduling calls, and more. Now, most of these tasks can be automated using AI.

AI can either suggest the ideal next steps to your customer support agents or even perform them instead of the team. It achieves this by analyzing and understanding the context of customer interactions, including the intent, sentiment, and emotion of the message. By doing so, AI ultimately reduces the cost borne by your company while letting your sales team focus on more strategic activities. 

Sales workflow suggestions with AI

Workflows help your business by setting up a series of predefined steps or tasks that can be automated to complete a process. In the context of CRM, workflows are triggered when a certain action occurs. For example, if a user registers for an account, this action automatically triggers a workflow to send them a welcome email.

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The impact of AI in setting and automating workflows has been nothing short of transformative. AI can make intelligent decisions with the help of machine learning and predictive analysis, which makes it all the more accurate and reliable. Even lead scoring can be done smarter using AI. Moreover, AI can adapt to changing scenarios and optimize its workflows in real-time, allowing your business to always stay one step ahead.

Elevate user experience through contextual AI 

It goes without saying that your sales team’s ultimate goal is to provide your customers with better buying experiences to keep them coming back for more. By understanding customers’ buying and behavioral patterns, AI can help you develop a communication plan that will allow your sales team to do just that. 

Using historical data, AI can help you determine the tone and context of a message, the best time and channel to contact customers, etc.

The human approach with contextual AI 

AI has evolved from a simple machine learning tool to a comprehensive content analysis model that makes intricate connections between data points, providing more contextual results. It aims to take a human approach to analyzing information by using intelligent learning rather than depending on statistical algorithms.

Contextual AI primarily works by making decisions based on emotional, situational, and cultural elements of the provided context. For example, AI chatbots respond to questions by understanding the context of the incoming message based on past interactions, customer preferences, message tone, etc.

A very important subset of contextual AI is email and call intelligence. Businesses receive hundreds of emails and calls every day, and it’s not realistic to expect your salespeople to track them all. 

This is where AI comes into play. 

In the case of emails, AI can analyze the tone and sentiment of the content and urge sales reps to act accordingly. It can also extract specific data from emails and capture it directly in your CRM tool. 

For example, if a customer sounds dissatisfied with the services offered, AI can alert the appropriate account owner and recommend that they follow up on the customer’s concerns. Additionally, AI can provide autocomplete suggestions for writing your sales emails.

Similarly, with the help of call transcription, you can transcribe calls into text, which is then stored in the CRM system for future use. Call intelligence can analyze the sentiment, intent, and tone of each call and provide a summary. 

For example, let’s say a prospective customer is passed from one sales rep to another due to unavoidable circumstances. At first, the new salesperson might not have the required knowledge to address the customer queries. But with call intelligence features, they can simply look at the AI-generated summary of the customer’s calls to get up to speed.

Challenges when implementing AI in CRM tools

Like every other technology, implementing AI in CRM systems also comes with drawbacks that organizations should carefully consider.

  • High implementation costs: The initial investment you need for AI technology can be substantial. This includes software acquisition and running costs, among other things. Additionally, you will also need to train employees to use these advanced tools effectively, which can further inflate costs.
  • Data privacy and compliance risks: AI systems often require access to large volumes of customer data to function effectively. This raises concerns regarding data privacy and compliance with regulations like the EU’s General Data Protection Regulation (GDPR). Mishandling data can result in legal repercussions and loss of customer trust. Hence, AI vendors need to be mindful of these risks, and customers must evaluate vendors’ privacy parameters carefully.
  • Potential for bias: AI algorithms have been known to operate via biases enshrined in the data initially fed into them. If historical data reflects certain prejudices or inequalities, AI can replicate these biases in customer interactions. This may lead to unfair treatment of specific customer segments, harm your relationships, and drive away potential clients.
  • Loss of personal touch: While AI can efficiently handle routine inquiries, it can lack the empathic qualities of real humans. Customers often appreciate personalized interactions, and over-reliance on automated systems can lead to frustration if their specific needs are not adequately addressed.
  • Dependence on quality data: The effectiveness of AI depends largely on the quality of the data it processes. Inaccurate or incomplete data can result in flawed insights and recommendations, ultimately impacting customer satisfaction and the effectiveness of your marketing strategies.
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Ethical considerations while implementing AI in CRM

Implementing AI in CRM raises several important ethical considerations that your company must address.

  • Data privacy and consent: Collecting and processing customer data for AI applications requires clear policies on data privacy. You must obtain informed consent from customers and ensure that their data is used transparently, securely, and in compliance with regulations.
  • Bias and fairness: AI systems can reflect existing biases present in training data and produce discriminatory outcomes. You must actively work to identify and mitigate biases to ensure fair treatment of all customers, regardless of other factors such as race, gender, or socioeconomic status.
  • Transparency: You must inform your customers about how AI is used in interactions, including the data that’s being collected. Providing clear explanations of how algorithms work can build trust and help customers understand how their data is being used.
  • Accountability: Establishing accountability in your company for AI-driven decisions is crucial. You should define who’s responsible for the outcomes of AI interactions and ensure that there are steps in place to address any deviations that arise from AI decisions.
  • Job displacement and impact on the workforce: The integration of AI into CRM can lead to concerns about job displacement for customer service representatives and other roles. Companies should consider the socioeconomic impact of this implementation and explore reskilling and upskilling opportunities for employees it affects.
  • Security risks: With an increase in data collection comes the heightened risk of data breaches and cyber attacks. You must prioritize cybersecurity measures to protect sensitive customer information from being misused.

Addressing these ethical considerations and challenges can help you implement AI in CRM responsibly, fostering trust and long-term customer relationships while adhering to ethical standards.

Staying ahead with the AI in CRM advantage

The future of CRM is here, and it is powered by AI.

Using AI in CRM allows you to move past human limitations when offering personalized and exceptional buying experiences to your customers. Embracing this technology will be key to staying ahead of your competitors and thriving in a rapidly evolving marketplace.

Uncover free CRM software options that can complement your AI-enabled CRM strategy in our 2024 guide.

Edited by Shanti S Nair

منبع: https://learn.g2.com/ai-in-crm